{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,23]],"date-time":"2026-09-23T16:15:00Z","timestamp":1790180100870,"version":"4.1.0"},"reference-count":35,"publisher":"World Scientific Pub Co Pte Lt","issue":"02","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Bifurcation Chaos"],"published-print":{"date-parts":[[2004,2]]},"abstract":"<jats:p>Recently, neurobiologists have discovered axons on neurons which synapse on the same neuron's dendrites \u2014 so-called autapses. It is not yet clear what functional significance autapses offer for neural behavior. This is an ideal case for using a physical simulation to investigate how an autapse alters the firing of a neuron. We simulated a neural basket cell via the Hodgkin\u2013Huxley equations and implemented an autapse which feeds back onto the soma of the neuron. The behavior of the cell was compared with and without autaptic feedback. Our artificial autapse neuron (AAN) displays oscillatory behavior which is not observed for the same model neuron without autapse. The neuron oscillates between two functional states: one where it fires at high frequency and another where firing is suppressed. This behavior is called \"spike bursting\" and represents a common pattern recorded from cerebral neurons.<\/jats:p>","DOI":"10.1142\/s0218127404009338","type":"journal-article","created":{"date-parts":[[2004,3,23]],"date-time":"2004-03-23T11:29:26Z","timestamp":1080041366000},"page":"623-633","source":"Crossref","is-referenced-by-count":76,"title":["AUTAPSE TURNS NEURON INTO OSCILLATOR"],"prefix":"10.1142","volume":"14","author":[{"given":"CHRISTOPH S.","family":"HERRMANN","sequence":"first","affiliation":[{"name":"Max\u2013Planck\u2013Institute of Cognitive Neuroscience, Postfach 500 355, 04303 Leipzig, Germany"},{"name":"Magdeburg University, P.O. Box 4120, 39016 Magdeburg, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"ANDREAS","family":"KLAUS","sequence":"additional","affiliation":[{"name":"Max\u2013Planck\u2013Institute of Cognitive Neuroscience, Postfach 500 355, 04303 Leipzig, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"219","published-online":{"date-parts":[[2011,11,20]]},"reference":[{"key":"rf1","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-8760(96)00051-7"},{"key":"rf2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.88.17.7834"},{"key":"rf4","doi-asserted-by":"publisher","DOI":"10.1038\/378075a0"},{"key":"rf5","volume-title":"Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems","author":"Dayan P.","year":"2001"},{"key":"rf6","unstructured":"R.\u00a0Eckhorn, Nonlinear Dynamics and Neural Networks, eds. H. 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